This dataset, Multi-Criteria Network Routing Dataset, is designed for research and analysis of secure and reliable data transmission in distributed networks. It supports the development and evaluation of routing optimization algorithms by incorporating key factors such as latency, bandwidth, security risks, trust scores, and energy efficiency.

The dataset includes 500 simulated network routing records, where each route is evaluated based on its performance and security attributes. It features a target column (Optimal_Route) that labels each routing decision as either Optimal (1) or Non-Optimal (0) based on predefined criteria.

Key Features: Route Characteristics: Source and destination nodes, latency, bandwidth. Security Metrics: Security risk score and trust score. Performance Indicators: Packet delivery ratio, end-to-end delay, energy consumption. Target Column: Classifies routes as Optimal (1) or Non-Optimal (0) based on multi-criteria evaluation.

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Route Optimization Software Market Size 2024-2028

The route optimization software market size is forecast to increase by USD 4.48 billion, at a CAGR of 18.5% between 2023 and 2028.

The market is experiencing significant growth as businesses in logistics, transportation, and supply chain management sectors increasingly adopt advanced solutions to enhance operational efficiency. Real-time reporting and analysis enable shippers, third-party logistics providers (3PLs), and carriers to make informed decisions, optimize routes, and reduce costs. However, the market faces challenges, including security concerns, as the increasing use of real-time data and cloud-based systems necessitates robust cybersecurity measures to protect sensitive information.
Companies must prioritize implementing secure solutions to mitigate potential risks and maintain customer trust. The dynamic market landscape presents both opportunities and challenges for businesses, requiring strategic planning and continuous innovation to capitalize on emerging trends and navigate obstacles effectively.

What will be the Size of the Route Optimization Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
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The market continues to evolve, driven by the increasing demand for efficient and effective logistics solutions across various sectors. Seamlessly integrated dynamic routing protocols enable real-time adjustments to changing traffic conditions and delivery priorities. Distance matrix calculations provide the foundation for optimizing delivery routes, while API documentation facilitates easy integration with other systems. Order assignment algorithms ensure optimal resource allocation, delivery time optimization keeps customers informed, and real-time traffic data enables proactive response to congestion. Geographic information systems and route optimization algorithms provide valuable insights for route planning, while route history reporting facilitates continuous improvement. Fuel consumption optimization, turn-by-turn navigation, and driver dispatch systems further enhance operational efficiency.

Capacity planning tools, delivery route planning, and route efficiency metrics enable organizations to optimize their logistics networks. Route visualization tools and SDK integration offer flexibility and customization, while map API integration and traffic pattern analysis provide real-time data for informed decision-making. Cloud-based routing platforms, shortest path algorithms, constraint-based routing, and last-mile delivery optimization address the unique challenges of complex logistics operations. ETA prediction models, automated route planning, route deviation detection, multi-stop route optimization, geofencing capabilities, and fleet management software offer additional features to streamline operations and improve customer satisfaction.

How is this Route Optimization Software Industry segmented?

The route optimization software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Deployment

  Cloud based
  On-premises


Geography

  North America

    US
    Canada


  Europe

    UK


  APAC

    China
    Japan


  Rest of World (ROW)

By Deployment Insights

The cloud based segment is estimated to witness significant growth during the forecast period.

Cloud-based route optimization software has become a game-changer in logistics and transportation industries, offering numerous benefits over traditional on-premises solutions. Dynamic routing protocols and real-time traffic data enable automated route planning, ensuring optimal delivery schedules and reduced fuel consumption. Order assignment algorithms and route optimization algorithms facilitate efficient delivery route planning, while capacity planning tools help manage fleet capacity. Geographic Information Systems (GIS) and map APIs provide accurate distance matrix calculations and traffic pattern analysis, ensuring the most efficient routes. Route history reporting and live route tracking offer valuable insights into route efficiency metrics, enabling continuous improvement. Route visualization tools and SDK integration simplify the integration process with existing systems.

Moreover, cloud-based platforms support multi-stop route optimization, geofencing capabilities, and last-mile delivery optimization, addressing the unique challenges of complex delivery networks. Constraint-based routing and shortest path algorithms cater to specific business requirements, while ETA prediction models and automated route planning ensure accurate and timely delivery commitments. Fleet managem

The global route planning and management software market size is valued at USD XXX million in 2023 and is expected to experience a CAGR of XX% during the forecast period 2023-2033. The market is driven by factors such as increasing demand for efficient and cost-effective route optimization, growing adoption of cloud-based solutions, and the need to improve customer satisfaction and loyalty. The market is segmented by type into route forecasting, density analysis, and others; by application into logistics and transportation, public works, and others; and by region into North America, South America, Europe, Middle East & Africa, and Asia Pacific. Key trends in the market include the adoption of artificial intelligence (AI) and machine learning (ML) to optimize routes, the integration of real-time data to improve accuracy, and the growing demand for mobile route planning solutions. Key market players include Descartes, RouteManager, GSMtasks, PTV, AMCS, Advotics, SPOTIO, FAST LEAN SMART, Routeique, GORILLADESK, Verizon Connect, Nomadia, Routific, Hedyla, Paragon, Detrack, SmartRoutes, LogiNext, and Route4Me. The market is expected to witness strong growth in the coming years, driven by the increasing adoption of route planning and management software solutions across various industries. Route planning and management software optimizes vehicle routing, improves delivery efficiency, and reduces operational costs. This industry is experiencing significant growth due to increasing demand for efficient logistics and transportation services.

This dataset contains 1000 rows capturing vehicle mobility, network connectivity, and environmental metrics in 5G-based Vehicular Ad Hoc Networks (VANETs). It is designed to support predictive and sustainable routing analysis.

Description: The dataset provides comprehensive information on vehicle movement, traffic conditions, and network performance. Each row corresponds to a unique timestamped vehicle record. It includes numerical, categorical, and target attributes relevant to routing decisions, energy consumption, and network reliability.

Number of Rows: 1000 Number of Columns: 15

Key Features:

Vehicle_ID: Unique identifier for each vehicle

Timestamp: Sequential timestamp of the record

Speed_km_h: Vehicle speed in kilometers per hour

Position_X_km / Position_Y_km: Vehicle position coordinates

Traffic_Density: Vehicles per km in the area

Link_Quality: Network connectivity strength (0-1)

Road_Type: Type of road (Highway, Urban, Rural)

Energy_Consumption_Wh_per_km: Energy usage per km

Latency_ms: Communication latency in milliseconds

Carbon_Emission_g_per_km: Estimated carbon emissions

Reliability_Score: Predicted link reliability (0-1)

Predicted_Position_X / Predicted_Position_Y: Next position predictions

Optimal_Route: Recommended route choice (Route A/B/C)

Shortest Route Analysis Of Dhaka City Roads Using Various Gis Techniques (Dataset And Sample Outputs)
This dataset falls under the category Public Transport Transport Network Geometries (Geodata).
It contains the following data: This repository is the dataset of the related paper "Shortest Route Analysis of Dhaka City Roads Using Various GIS Techniques".The data presented here are collected and gathered together from several separate locations. All the probable original sources of the dataset are open-source or free to distribute licensed. The dataset has the following items: 1. Road network of Dhaka city. 2. Bus Route network of Dhaka city. 3. Future metro Route network of Dhaka city. 4. All the bus stands in Bangladesh. 5. All planned metro station in Dhaka city. 6. The output of some sample random two points shortest or cheapest path from the related paper.
This dataset was scouted on 2022-02-23 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://data.mendeley.com/datasets/j5b93k2xhk/1\ Please note: This link leads to an external resource. If you experience any issues with its availability, please try again later.

The size of the Vehicle Routing and Scheduling Applications market was valued at USD XXX million in 2023 and is projected to reach USD XXX million by 2032, with an expected CAGR of XX% during the forecast period.

This dataset represents a 5G-enabled Vehicular Ad Hoc Network (VANET) environment that integrates vehicular mobility (SUMO) with 5G and device-to-device (D2D) communication models (NS-3/Veins). It contains 1800 rows of vehicle mobility, communication, and energy features under diverse traffic and network conditions.

The dataset includes multiple vehicle types (cars, buses, trucks, motorcycles, ambulances, fire trucks, and police cars) and records parameters such as vehicle speed, acceleration, density, signal strength (RSSI), SNR, link duration, throughput, end-to-end delay, packet delivery ratio, residual energy, and control overhead.

A target column (Efficient_Route) is provided for machine learning-based routing analysis.

ABSTRACT The Vehicle Routing Problem (VRP) is a classical problem, and when the number of customers is very large, the task of finding the optimal solution can be extremely complex. It is still necessary to find an effective way to evaluate the quality of solutions when there is no known optimal solution. This work presents a suggestion to analyze the quality of vehicle routes, based only on their geometric properties. The proposed descriptors aim to be invariants in relation to the amount of customers, vehicles and the size of the covered area. Applying the methodology proposed in this work it is possible to obtain the route and, then, to evaluate the quality of solutions obtained using computer vision. Despite considering problems with different configurations for the number of customers, vehicles and service area, the results obtained with the experiments show that the proposal is useful for classifying the routes into good or bad classes. A visual analysis was performed using the Parallel Coordinates and Viz3D techniques and then a classification was performed by a Backpropagation Neural Network, which indicated an accuracy rate of 99.87%.

The size of the Dispatch Routing Software market was valued at USD 2593.2 million in 2024 and is projected to reach USD 4649.89 million by 2033, with an expected CAGR of 8.7 % during the forecast period.

Discover the booming Vehicle Routing & Scheduling (VR&S) applications market! This in-depth analysis reveals a $15B market in 2025, projected to grow at a 12% CAGR, driven by e-commerce, AI, and optimization needs. Learn about key players, trends, and regional insights to leverage this lucrative sector.

Problem Statement description that i worked on to make this data: The Automated Bus Scheduling and Route Management System is designed to streamline and automate the scheduling and route planning process for the Delhi Transport Corporation (DTC). This project aims to improve operational efficiency, reduce errors, and enhance the reliability of bus services by replacing the current manual methods with an automated software solution. The system leverages algorithms, data analytics, and Geographic Information System (GIS) technologies to manage both linked and unlinked duty scheduling and optimize route planning.

Feel free to play with this!

Blockchain data query: Cross-chain messaging routing analysis; Q3 '24

The Route Planning and Management Software market is experiencing robust growth, driven by the increasing need for efficient logistics and optimized delivery routes across diverse sectors. The market, estimated at $15 billion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. Firstly, the e-commerce boom necessitates sophisticated route optimization to manage surging delivery volumes and meet customer expectations for faster shipping. Secondly, the rise of last-mile delivery challenges further intensifies the demand for intelligent route planning solutions capable of handling complex delivery networks and minimizing operational costs. Thirdly, advancements in technologies like AI, machine learning, and real-time GPS tracking enhance route planning accuracy and efficiency, enabling businesses to make data-driven decisions and improve overall operational performance. Finally, growing government regulations emphasizing efficient resource utilization and reduced environmental impact are driving adoption of route optimization software across public works and transportation sectors. The market segmentation reveals strong growth in both application and type. The logistics and transportation sector dominates the application segment, followed by public works. Route forecasting features are highly sought after, reflecting the importance of predictive analytics in mitigating potential delays and optimizing delivery schedules. Competition in this market is intense, with numerous established and emerging players vying for market share. While established players like Descartes and PTV benefit from brand recognition and extensive customer bases, newer companies like Route4Me and Routific are gaining traction through innovative features and competitive pricing. Regional market analysis indicates a strong presence in North America and Europe, with Asia Pacific emerging as a high-growth region due to rapid e-commerce adoption and infrastructure development. However, factors such as high initial investment costs and the need for specialized technical expertise can act as restraints, particularly for smaller businesses. Overall, the Route Planning and Management Software market presents significant opportunities for growth and innovation in the coming years.

This dataset provides comprehensive synthetic records of last-mile delivery routes, including geospatial coordinates, stop sequences, package details, resource allocation, and contextual factors like weather and traffic. It is optimized for machine learning applications in route recommendation, delay prediction, and logistics resource planning, supporting both operational analytics and AI-driven optimization.

This dataset contains Vehicular Ad Hoc Networks (VANETs) for evaluating energy-efficient and resilient routing in intelligent transportation systems. It contains 3000 data points with 12 features and 1 target column, reflecting vehicle mobility, network performance, and environmental impact. The dataset can be used for routing analysis, simulation studies, or supervised modeling of routing efficiency.

Column Descriptions:

Vehicle_ID – Unique identifier assigned to each vehicle in the simulation.

Timestamp – Time (in seconds) when the vehicle’s status is recorded.

Position_X – X-coordinate representing the vehicle’s location on the map.

Position_Y – Y-coordinate representing the vehicle’s location on the map.

Speed – Current speed of the vehicle in km/h.

Acceleration – Instantaneous acceleration of the vehicle in m/s².

Cluster_ID – Identifier for the cluster or group the vehicle belongs to during dynamic routing.

Routing_Metric – A score (0–1) reflecting path suitability based on local routing decisions.

Energy_Consumption – Energy used by the vehicle for communication in Joules.

Packet_Delivery_Ratio – Percentage of successfully delivered packets (70–100%).

Throughput – Amount of data transmitted per unit time in Mbps.

Latency – End-to-end transmission delay in milliseconds.

Carbon_Emission – Estimated carbon footprint of vehicle communication in grams of CO₂.

Routing_Efficiency (Target) – Overall efficiency of the chosen route (0–1), combining energy usage, latency, throughput, and packet delivery ratio.

Blockchain data query: 5. Trade routing efficiency analysis

This dataset presents the Spatial Network Analysis for Multimodal Urban Transport Systems (SNAMUTS) route segments for the year of 2016. Route segments are a public transport link between two adjacent activity nodes or other network nodes. A numbered public transport route is usually made up of a sequence of consecutive route segments The SNAMUTS methodology has been developed as a planning and decision-making support tool. It determines accessibility performance from a user perspective, bearing in mind that different users sometimes have different needs: some may value speed more than anything else, some may require barrier-free access as their first priority, others may be drawn primarily to services that are legible and have a high profile in the urban realm. Good accessibility is often the result of a balance and integration of these sometimes competing, sometimes complementary claims on the usability of the land use-transport system. The analysis includes a set of tasks and measurements that highlight the contribution of the public transport network and service development from a range of perspectives. These are known as the eight key SNAMUTS indicators, they include: Service Intensity

This dataset provides granular logistics route data, including provider information, origin and destination addresses, delivery times, costs, and optimization status. It enables detailed analysis of route efficiency, cost reduction strategies, and supply chain performance benchmarking for logistics providers and shippers.

School Bus Routing Software Market Outlook

According to our latest research, the school bus routing software market size reached USD 285.6 million globally in 2024, with a robust year-on-year expansion. The market is projected to grow at a CAGR of 11.2% from 2025 to 2033, reaching a forecasted value of USD 739.3 million by 2033. This remarkable growth is primarily driven by the increasing adoption of digital solutions to streamline school transportation operations, improve safety, and reduce operational costs. The market’s momentum is further fueled by the demand for real-time tracking, route optimization, and enhanced communication between schools, parents, and transportation providers.

One of the most significant growth factors in the school bus routing software market is the increasing emphasis on student safety and security. Parents, school administrators, and regulatory authorities are demanding greater transparency and control over student transportation. This has led to a surge in the adoption of advanced routing software equipped with GPS tracking, real-time notifications, and automated alerts for deviations or emergencies. The integration of such features not only reassures parents but also enables schools to comply with stringent safety regulations, minimize liability, and respond rapidly to unforeseen circumstances. As a result, software vendors are continuously innovating to offer more robust and user-friendly solutions, further propelling market growth.

Another key driver is the operational efficiency and cost savings provided by school bus routing software. Manual route planning is often time-consuming, prone to errors, and leads to inefficient resource utilization. By leveraging sophisticated algorithms and data analytics, these software platforms optimize routes, minimize fuel consumption, reduce travel time, and maximize bus occupancy. This directly translates into significant cost reductions for school districts and private operators, especially in regions where transportation budgets are under scrutiny. Additionally, the ability to dynamically adjust routes in response to traffic conditions, weather, or last-minute changes ensures smoother operations and higher service reliability, making the investment in routing software increasingly attractive.

The growing trend toward digital transformation in the education sector is also catalyzing the adoption of school bus routing software. Schools are increasingly embracing cloud-based platforms and mobile applications to enhance administrative efficiency and parent engagement. The integration of routing software with other school management systems allows for seamless data sharing, automated reporting, and improved decision-making. Furthermore, the COVID-19 pandemic accelerated the shift to digital platforms, as schools sought to minimize contact and manage staggered schedules. This shift has created a long-term demand for scalable, flexible, and remote-accessible routing solutions, ensuring sustained growth for the market in the coming years.

From a regional perspective, North America currently dominates the school bus routing software market, accounting for the largest share in 2024 due to its advanced technological infrastructure, high education spending, and stringent student safety regulations. However, Asia Pacific is emerging as the fastest-growing region, driven by rapid urbanization, increasing school enrollments, and government initiatives to modernize educational transportation systems. Europe also presents significant growth opportunities, particularly in countries prioritizing sustainability and eco-friendly transportation. Latin America and the Middle East & Africa are gradually adopting these solutions, supported by rising investments in educational infrastructure and growing awareness of digital solutions. Overall, the global market is poised for robust expansion, with regional dynamics shaping the competitive landscape and innovation trajectory.

Component Analysis

The school bus

Internet Routing Analytics Market Outlook

According to our latest research, the global Internet Routing Analytics market size reached USD 1.86 billion in 2024, reflecting robust adoption across diverse sectors. The market is expected to grow at a CAGR of 16.2% during the forecast period, propelling the market to an estimated USD 7.15 billion by 2033. This significant growth is primarily driven by the escalating demand for real-time network visibility, the proliferation of cloud-based services, and increasing concerns over network security and compliance. As organizations worldwide strive to optimize network performance and manage complex, distributed infrastructures, the need for advanced Internet Routing Analytics solutions continues to intensify.

The primary growth factor for the Internet Routing Analytics market is the surge in data traffic and the expansion of interconnected networks, especially with the rise of IoT devices and cloud computing. Enterprises and service providers are under mounting pressure to maintain seamless network operations, minimize downtime, and ensure rapid fault detection and resolution. Internet Routing Analytics solutions provide critical insights into network behavior, enabling proactive management and optimization. The capability to analyze routing protocols, monitor traffic patterns, and detect anomalies in real-time is invaluable for maintaining service quality and meeting stringent SLAs. As digital transformation accelerates, the reliance on these analytics tools is becoming indispensable for both large enterprises and small-to-medium businesses.

Another key driver is the increasing complexity of network architectures, fueled by hybrid and multi-cloud environments. Organizations are deploying a mix of on-premises, private, and public cloud resources, resulting in highly fragmented and dynamic network topologies. This complexity necessitates sophisticated analytics platforms capable of providing a unified view across heterogeneous environments. Internet Routing Analytics solutions bridge this gap by aggregating data from various sources, correlating events, and providing actionable intelligence. The shift towards software-defined networking (SDN) and network function virtualization (NFV) further amplifies the need for advanced analytics, as traditional monitoring tools are often inadequate for these agile, programmable infrastructures.

Security and compliance considerations are also propelling market growth. With increasing cyber threats targeting network infrastructure, organizations are prioritizing solutions that offer deep visibility into routing anomalies, unauthorized access attempts, and potential vulnerabilities. Internet Routing Analytics platforms are evolving to integrate advanced threat detection, policy compliance monitoring, and automated response capabilities. Regulatory mandates around data privacy and network security are compelling enterprises, especially in regulated industries such as finance and healthcare, to invest in comprehensive analytics solutions. The convergence of routing analytics with security operations is expected to be a major trend shaping the market over the next decade.

From a regional perspective, North America continues to dominate the Internet Routing Analytics market, driven by early technology adoption, the presence of leading solution providers, and substantial investments in network infrastructure modernization. However, Asia Pacific is emerging as the fastest-growing region, fueled by rapid digitalization, expanding telecom networks, and government initiatives to build smart cities and enhance connectivity. Europe remains a significant contributor, particularly in sectors such as telecommunications and cloud services, with a strong focus on data privacy and regulatory compliance. Latin America and the Middle East & Africa are witnessing steady growth, supported by increasing internet penetration and infrastructure development, albeit at a comparatively moderate pace.

Component Analysis

The Internet Routing Analytics market is segmented by component into software, hardware, and services, each playing a critical role in the delivery and performance of analytics solutions. The software segment constitutes the largest share, driven by the growing adoption of advanced analytics platforms that leverage artificial intelligence, machine learning, and big data technologies. These platforms are designed to process vast amounts of routing data, identif